by Dr. Stylianos Kazazis, UBITECH
The modern world is increasingly data and information-driven, while the growth of our interconnected societies is underpinned by the continuous improvement of digital computational technologies and architectures. This comprehensive digitization will allow for the optimization of energy and resource usage, helping to alleviate the strain on planetary resources. The ever-growing number of variables and constraints in real-life optimization problems, however, requires improved computational efficiency, that conventional von Neumann architectures struggle to provide as they are reaching their scalability and power efficiency limits. Beyond traditional computing platforms, several optical classical and quantum spin simulators have been proposed as alternatives and are being actively developed, promising superior speeds along with robust reconfigurability, low power consumption, and hardwired parallel processing. These systems aim to provide faster and cost-effective computational solutions for specialised problem classes and cases of data-intensive (big-data) tasks and optimizations.
Optical annealer devices map a system observable to a minimizor variable of a given problem and allow the system to naturally evolve towards the minimum of the mapped cost function. In this case, the inherently fast dynamics of these systems dictate the time to the solution, which can be orders of magnitude faster than classical computers, especially for large numbers of optimization elements. Effectively such systems are analogue machines that bootstrap the underlying physics of well-studiedphysical systems which can be efficiently controlled by employing mature advances of optoelectronic technologies.
HEISINGBERG proposes an alternative approach to existing quantum simulators exploiting the mature technology of spatial light modulation. The latter introduces a range of advantages that mitigate systemic bottlenecks associated with the scalability and applicability of these devices, with the most pronounced of these being: i) cost effective, ii) easily programmable, iii) environmentally friendly (low power consumption <1kW), iv) scalability, and v) noncryogenic operation. Moreover, the investigation into novel annealing algorithms for XY Hamiltonians will contribute to the growth of quantum algorithms employed by state-of-the-art quantum annealing machines.
In this context, HEISINGBERG aims to develop a novel information processing platform, based on the XY spin Hamiltonian, as a scalable energy efficient alternative to current state of the art quantum simulators, considering experimental, theoretical, algorithmic and control aspects. The project is designed to fully develop and deliver:
i. the core optoelectronic system hardware
ii. a novel approach to encode spins and control their mutual couplings,
iii. custom-tailored algorithms for the optimisation of the annealing process as well as the optimal mapping of real-life problems,
iv. a generalisation of the existing theoretical model to account for the quantum operation regime,
v. advances in experimental realisation and measurements for the quantum operation, and finally,
vi. a dedicated control and interfacing software for the robust deployment of the machine.
